Liability regimes in the age of AI: a use-case driven analysis of the burden of proof

TL;DR

This paper examines the challenges of establishing liability in AI-related incidents, highlighting the need to adapt legal frameworks to better support victims due to AI's inherent characteristics.

Contribution

It introduces a case-study driven methodology to analyze liability issues in AI, proposing revisions to current regimes to reduce victims' burden of proof.

Findings

Liability challenges are significant in AI due to opacity and unpredictability.

Case studies reveal difficulties in proving causation in AI incidents.

Revisions to liability regimes can better protect victims of AI-related harm.

Abstract

New emerging technologies powered by Artificial Intelligence (AI) have the potential to disruptively transform our societies for the better. In particular, data-driven learning approaches (i.e., Machine Learning (ML)) have been a true revolution in the advancement of multiple technologies in various application domains. But at the same time there is growing concern about certain intrinsic characteristics of these methodologies that carry potential risks to both safety and fundamental rights. Although there are mechanisms in the adoption process to minimize these risks (e.g., safety regulations), these do not exclude the possibility of harm occurring, and if this happens, victims should be able to seek compensation. Liability regimes will therefore play a key role in ensuring basic protection for victims using or interacting with these systems. However, the same characteristics that make AI systems inherently risky, such as lack of causality, opacity, unpredictability or their self and continuous learning capabilities, may lead to considerable difficulties when it comes to proving causation. This paper presents three case studies, as well as the methodology to reach them, that illustrate these difficulties. Specifically, we address the cases of cleaning robots, delivery drones and robots in education. The outcome of the proposed analysis suggests the need to revise liability regimes to alleviate the burden of proof on victims in cases involving AI technologies.